DE 698 30 583 T2 discloses an image data processing method that involves receiving input data which are divided into elementary units of information. Reference is made therein to the difference in suitability of the HLS color space and the RGB color space for various analyses.
From DE 44 19 395 A1 a method for analyzing color images for the purpose of object recognition is known, in which RGB image values are converted to the HSI color space to enable individual pixels to be classified based on their color.
DE 102 39 801 A1 teaches a method for extracting texture features from a multichannel image. According to a second embodiment, features are generated for the classification, which are calculated in the RGB space based on a color distance measure and in the HSV space using binary masks that are generated there.
In Selvarasu, N. et al. “Euclidean Distance Based Color Image Segmentation of Abnormality Detection from pseudo Color Thermographs”, International Journal of Computer Theory and Engineering, Vol. 2, No. 4, August 2010, 1793-8201, the use of the Euclidean distance for classifying individual pixels is described. In that case, a representative pixel is selected, which is used for calculating the Euclidean distance for every other pixel. If the distance is less than or equal to a predetermined threshold value the pixel is retained, and if not it is removed, so that in the end, only one segmented zone can be seen. Only one color space is used in this process. The segmentation is carried out based solely on the threshold value for the clearance. The interval for the hue is disregarded.
In Zakir, U. et al. “Road sign segmentation based on color spaces: A Comparative Study”, Proceedings of the 11th Lasted International Conference on Computer Graphics and Imaging, Innsbruck, Austria, 2010, the combination of the color value from the HSV color space with the chrominance from the YUV color space is described by an AND operation. In this case only intervals are used for segmentation.
In Zhan, Chi et al., “A new method of color image segmentation based on intensity and hue clustering”, Pattern Recognition, 2000, Proceedings 15th International Conference, Vol. 3, IEEE, 2000, the correlation between hue and intensity is described. In this case, these values are determined within the HSI color space.